Job Description

Data Scientist, Inference

At Lyft, our mission is to improve people’s lives with the world’s best transportation. To do this, we start with our own community by creating an open, inclusive, and diverse organization.

Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft work in dynamic environments, where we embrace moving quickly to build the world’s best transportation. We take on a variety of problems ranging from shaping long-term business strategy with data, making short-term critical decisions, and building algorithms/models that power our internal and external products. 

We are looking for a Data Scientist to join the Central Market Management (CMM) team, and drive the measurement of return-on-investment of various growth levers (e.g. rider pricing, driver pay, acquisition and retention incentives). The CMM team is responsible for managing the P&L of the business by making optimal investment decisions to trade-off long-term growth and short-term profitability.

As a data scientist, you’ll help develop the vision, set roadmaps, and lead execution for projects in Central Market Management. You’ll partner closely with product, engineering, and business leaders to build and scale our products and systems, shape the long-term strategy and deliver business goals.  You’ll be hands-on to build models that leverage observational and experimental causal inference methods, productionize pipelines, and integrate their results with decision-making frameworks. The ideal candidate should have strong experience developing and applying Causal Inference methods,  embrace moving fast with an entrepreneur mindset, and be hands-on to make things happen.  

Responsibilities: 

Collaborate with stakeholders from a diverse set of teams to design new experimental and observational methods to improve Lyft’s measurement of long-term efficiency of investments. Advise teams on best practices. Be a thought leader and go-to expert for users
Build observational and experimental causal inference models and integrate their outputs into investment decision-making frameworks
Provide coaching and technical guidance for the team
Prioritize and lead deep dives into our data to uncover new product and business opportunities
Facilitate and foster data-driven and informed decision making and prioritization

Experience: 

Advanced degree in a quantitative field like statistics, economics, computer science, operations research, or engineering; or relevant work experience
5+ years of hands-on industry experience in causal inference or data science
Track record of using statistics and guiding teams through unstructured technical problems to deliver business impact

Benefits:

Great medical, dental, and vision insurance options
Mental health benefits
Family building benefits
In addition to 12 observed holidays, salaried team members have unlimited paid time off, hourly team members have 15 days paid time off
401(k) plan to help save for your future
18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
Pre-tax commuter benefits
Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program